environment.yml

name: contrastive_planning
channels:
  - conda-forge
  - nvidia
  - pytorch
dependencies:
  - python=3.9
  - jax=0.4.23
  - jaxlib=*=*cuda*
  - cuda-nvcc
  - pytorch=2.1
  - einops=0.7.0
  - labmaze=1.0.6
  - lcms2=2.16
  - opencv=4.9.0
  - glew=2.1.0
  - scikit-learn=1.4.1.post1
  - dm-env=1.6
  - swig=4.2.0
  - cython<3
  - mesalib=23.2.1
  - tqdm=4.66.2
  - torchvision=0.16.2
  - matplotlib=3.8.3
  - tensorboard=2.16.2
  - seaborn=0.13.2
  - lockfile=0.12.2
  - h5py=3.10.0
  - torchmetrics=1.2.1
  - google-auth-oauthlib=1.2.0
  - dm-haiku=0.0.11
  - setuptools==65.5.0
  - pip=21.0
  - pip:
    - pybullet==3.2.5
    - imageio==2.32.0
    - gym==0.19.0
    - mujoco==2.2.0
    - mujoco-py==2.0.2.5
    - mjrl @ git+https://github.com/aravindr93/mjrl@3871d93763d3b49c4741e6daeaebbc605fe140dc
    - d4rl==1.1
variables:
  MUJOCO_GL: glfw
  PYOPENGL_PLATFORM: glfw
  TF_FORCE_GPU_ALLOW_GROWTH: "true"
  XLA_PYTHON_CLIENT_PREALLOCATE: "false"
  PYTHONFAULTHANDLER: 1